Modeling emergency management data by UML as an extension of geographic data sharing model: AST approach

Applying GIS functionality provides a powerful decision support in various application areas and the basis to integrate policies directed to citizens, business, and governments. The focus is changing toward integrating these functions to find optimal solutions to complex problems. As an integral part of this approach, geographic data sharing model for Turkey were developed as a new approach that enables using the data corporately and effectively. General features of this model are object-oriented model, based on ISO/TC211 standards and INSPIRE Data Specifications, describing nationwide unique object identifiers, and defining a mechanism to manage object changes through time. The model is fully described with Unified Modeling Language (UML) class diagram. This can be a starting point for geographic data providers in Turkey to create sector models like Emergency Management that has importance because of the increasing number of natural and man-made disasters. In emergency management, this sector model can provide the most appropriate data to many "Actors" that behave as emergency response organizations such as fire and medical departments. Actors work in "Sectors" such as fire department and urban security. Each sector is responsible for "Activities" such as traffic control, fighting dire, emission, and so on. "Tasks" such as registering incident, fire response, and evacuating area are performed by actors and part of activity. These tasks produce information for emergency response and require information based on the base data model. By this way, geographic data models of emergency response are designed and discussed with "Actor-Sector-Activity-Task" classes as an extension of the base model with some cases from Turkey

A Method for Deriving Trip Destinations and Modes for GPS-based Travel Surveys

This chapter contributes to the improvement of GPS-based travel surveying by introducing a combined method of GPS, GIS and web-based user interaction, which has been applied in large- scale fieldwork in the netherlands. With over 1000 participants, as far as we know, this is the first time that a GPS-based method that measures travel mode choice as well as the location and type of destinations that are visited has been used on such a large scale. The chapter focuses in particular on the identification of travel modes and destinations, which is still an under-researched issue. Our approach concentrates on the issue of deriving and validating the purpose of trip destinations and travel modes, while also allowing reliable multi-day data collection. The method consists of an interpretation process and a validation process. The interpretation process uses spatial data (e.g. railways, shops) and characteristics of the respondents (e.g. home address, possession of cars) to interpret data from the logs. The travel behaviour data that result from this interpretation round can be adjusted and added to by the respondents in a validation application. The link between both processes is interactive; when new individual characteristics (e.g. the address of a friend’s house) are entered by the respondents, these characteristics will be used for further interpretation of the data. The remainder of this chapter is structured as follows. The following section gives an overview of the advantages and drawbacks of current GPS-based data collection methods that are suitable for measuring choice of travel mode and/or trip destinations. The subsequent section describes the GPS-based method that we developed and in section four the value of our method is evaluated by presenting the results of the fieldwork we recently undertook. The results are compared with results from an internet survey that was carried out at an earlier date and also with the Dutch Travel Survey (DTS) that uses paper diaries. The chapter ends with conclusions on the use of GPS-based methods for the collection of travel behaviour data and a discussion of future possibilities

Monet And Its Geographic Extensions: a Novel Approach to High Performance GIS Processing

We describe Monet, a novel database system, designed to get maximum performance out of today's workstations and symmetric multiprocessors. Monet is a type- and algebra-extensible database system using the Decomposed Storage Model (DSM) and employing shared memory parallelism. It applies purely main-memory algorithms for processing and uses OS virtual memory primitives for handling large data. Monet provides many options in memory management and virtual-memory clustering strategies to optimize access to its tables. We discuss how these unusual features impacted the design, implementation and performance of a set of GIS extension modules, that can be loaded at runtime in Monet, to obtain a functional complete GIS server. The validity of our approach is shown by excellent performance figures on both the Regional and National Sequoia storage benchmark. 1 Introduction In recent years, consensus has been reached in the GIS community about the advantages of extensible database systems. In..

Linking spatial data: automated conversion of geo-information models and GML data to RDF

Linked data provide an alternative route for the dissemination of spatial information compared to the traditional SOA-based SDI approach. The traditional approach has provided a wealth of standardized and structured location data based on Geography Markup Language (GML), while linked data provides an open mechanism for sharing and combining this data with anything, once the data is available as linked data. The first part of the paper focuses on deriving linked data from GML data. In the second part, we study how more meaningful data, expressed in Resource Description Framework (RDF) can be created from GML, given the underlying information model, by transforming it from Unified Modeling Language (UML) to Web Ontology Language (OWL)

A semantic-rich multi-scale information model for topography

National mapping agencies maintain topographic data sets at different scales. Keeping the data sets consistent, for example by means of automated update propagation, requires formal knowledge on how the different data sets relate to each other. This article presents a multi-scale information model that, first, integrates the data states at the different scales and, second, formalises semantics on scale transitions. This is expressed using the Unified Modelling Language (UML) class diagrams, complemented with Object Constraint Language (OCL). Based on a requirement analysis using the needs of the Netherlands' Kadaster as case study, this article examines several modelling alternatives and selects the optimal modelling approach for a multi-scale information model for topography. The model is evaluated through a prototype database implementation. The results show that UML/OCL provides an appropriate formalism to model rich semantics on both multi-scale data content and scale transitions, which can be used for guarding consistency based on automated generalisation of updates. Further research is required to express generalisation specifications that are currently not formalised and that are only available in software code or as cartographers' knowledge